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Author's title

Author*Unverified author*
R Software Modulerwasp_smp.wasp
Title produced by softwareStandard Deviation-Mean Plot
Date of computationThu, 26 Apr 2012 17:49:31 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2012/Apr/26/t1335477169tebecpop5ali0v4.htm/, Retrieved Sun, 28 Apr 2024 20:16:06 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=164956, Retrieved Sun, 28 Apr 2024 20:16:06 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact92
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Standard Deviation-Mean Plot] [] [2012-04-26 21:49:31] [3f9379635061ebc5737ab9ab2503b0b0] [Current]
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Dataseries X:
65
65.3
62.9
63.5
62.1
59.3
61.6
61.5
60.1
59.5
62.7
65.5
63.8
63.8
62.7
62.3
62.4
64.8
66.4
65.1
67.4
68.8
68.6
71.5
75
84.3
84
79.1
78.8
82.7
85.3
84.5
80.8
70.1
68.2
68.1
72.3
73.1
71.5
74.1
80.3
80.6
81.4
87.4
89.3
93.2
92.8
96.8
100.3
95.6
89
87.4
86.7
92.8
98.6
100.8
105.5
107.8
113.7
120.3




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 1 seconds \tabularnewline
R Server & 'AstonUniversity' @ aston.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164956&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]1 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'AstonUniversity' @ aston.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164956&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164956&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time1 seconds
R Server'AstonUniversity' @ aston.wessa.net







Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
162.41666666666672.156947899793656.2
265.63333333333332.936086861897329.2
378.40833333333336.5120110471948617.2
482.73333333333338.9862858475197325.3
599.87510.536613653006733.6

\begin{tabular}{lllllllll}
\hline
Standard Deviation-Mean Plot \tabularnewline
Section & Mean & Standard Deviation & Range \tabularnewline
1 & 62.4166666666667 & 2.15694789979365 & 6.2 \tabularnewline
2 & 65.6333333333333 & 2.93608686189732 & 9.2 \tabularnewline
3 & 78.4083333333333 & 6.51201104719486 & 17.2 \tabularnewline
4 & 82.7333333333333 & 8.98628584751973 & 25.3 \tabularnewline
5 & 99.875 & 10.5366136530067 & 33.6 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164956&T=1

[TABLE]
[ROW][C]Standard Deviation-Mean Plot[/C][/ROW]
[ROW][C]Section[/C][C]Mean[/C][C]Standard Deviation[/C][C]Range[/C][/ROW]
[ROW][C]1[/C][C]62.4166666666667[/C][C]2.15694789979365[/C][C]6.2[/C][/ROW]
[ROW][C]2[/C][C]65.6333333333333[/C][C]2.93608686189732[/C][C]9.2[/C][/ROW]
[ROW][C]3[/C][C]78.4083333333333[/C][C]6.51201104719486[/C][C]17.2[/C][/ROW]
[ROW][C]4[/C][C]82.7333333333333[/C][C]8.98628584751973[/C][C]25.3[/C][/ROW]
[ROW][C]5[/C][C]99.875[/C][C]10.5366136530067[/C][C]33.6[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164956&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164956&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Standard Deviation-Mean Plot
SectionMeanStandard DeviationRange
162.41666666666672.156947899793656.2
265.63333333333332.936086861897329.2
378.40833333333336.5120110471948617.2
482.73333333333338.9862858475197325.3
599.87510.536613653006733.6







Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-12.134268700636
beta0.235947452396998
S.D.0.0373038274124022
T-STAT6.32501994469752
p-value0.00798954882682523

\begin{tabular}{lllllllll}
\hline
Regression: S.E.(k) = alpha + beta * Mean(k) \tabularnewline
alpha & -12.134268700636 \tabularnewline
beta & 0.235947452396998 \tabularnewline
S.D. & 0.0373038274124022 \tabularnewline
T-STAT & 6.32501994469752 \tabularnewline
p-value & 0.00798954882682523 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164956&T=2

[TABLE]
[ROW][C]Regression: S.E.(k) = alpha + beta * Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-12.134268700636[/C][/ROW]
[ROW][C]beta[/C][C]0.235947452396998[/C][/ROW]
[ROW][C]S.D.[/C][C]0.0373038274124022[/C][/ROW]
[ROW][C]T-STAT[/C][C]6.32501994469752[/C][/ROW]
[ROW][C]p-value[/C][C]0.00798954882682523[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164956&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164956&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: S.E.(k) = alpha + beta * Mean(k)
alpha-12.134268700636
beta0.235947452396998
S.D.0.0373038274124022
T-STAT6.32501994469752
p-value0.00798954882682523







Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-13.6537841131305
beta3.52723753332156
S.D.0.638514338435839
T-STAT5.52413206876794
p-value0.0116863250232362
Lambda-2.52723753332156

\begin{tabular}{lllllllll}
\hline
Regression: ln S.E.(k) = alpha + beta * ln Mean(k) \tabularnewline
alpha & -13.6537841131305 \tabularnewline
beta & 3.52723753332156 \tabularnewline
S.D. & 0.638514338435839 \tabularnewline
T-STAT & 5.52413206876794 \tabularnewline
p-value & 0.0116863250232362 \tabularnewline
Lambda & -2.52723753332156 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=164956&T=3

[TABLE]
[ROW][C]Regression: ln S.E.(k) = alpha + beta * ln Mean(k)[/C][/ROW]
[ROW][C]alpha[/C][C]-13.6537841131305[/C][/ROW]
[ROW][C]beta[/C][C]3.52723753332156[/C][/ROW]
[ROW][C]S.D.[/C][C]0.638514338435839[/C][/ROW]
[ROW][C]T-STAT[/C][C]5.52413206876794[/C][/ROW]
[ROW][C]p-value[/C][C]0.0116863250232362[/C][/ROW]
[ROW][C]Lambda[/C][C]-2.52723753332156[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=164956&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=164956&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Regression: ln S.E.(k) = alpha + beta * ln Mean(k)
alpha-13.6537841131305
beta3.52723753332156
S.D.0.638514338435839
T-STAT5.52413206876794
p-value0.0116863250232362
Lambda-2.52723753332156



Parameters (Session):
par1 = 12 ;
Parameters (R input):
par1 = 12 ;
R code (references can be found in the software module):
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
arr <- array(NA,dim=c(par1,np))
j <- 0
k <- 1
for (i in 1:(np*par1))
{
j = j + 1
arr[j,k] <- x[i]
if (j == par1) {
j = 0
k=k+1
}
}
arr
arr.mean <- array(NA,dim=np)
arr.sd <- array(NA,dim=np)
arr.range <- array(NA,dim=np)
for (j in 1:np)
{
arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
}
arr.mean
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
bitmap(file='test1.png')
plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
dev.off()
bitmap(file='test2.png')
plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Section',header=TRUE)
a<-table.element(a,'Mean',header=TRUE)
a<-table.element(a,'Standard Deviation',header=TRUE)
a<-table.element(a,'Range',header=TRUE)
a<-table.row.end(a)
for (j in 1:np) {
a<-table.row.start(a)
a<-table.element(a,j,header=TRUE)
a<-table.element(a,arr.mean[j])
a<-table.element(a,arr.sd[j] )
a<-table.element(a,arr.range[j] )
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[1]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'beta',header=TRUE)
a<-table.element(a,lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,2])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'T-STAT',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,3])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=TRUE)
a<-table.element(a,summary(lnlm1)$coefficients[2,4])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Lambda',header=TRUE)
a<-table.element(a,1-lnlm1$coefficients[[2]])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')